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distilbert-base-uncased-finetuned-AS_sentences

Text Classification
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PyTorch
TensorBoard
distilbert
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@@ -17,7 +17,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0018
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  - Accuracy: 1.0
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  - F1: 1.0
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@@ -50,206 +50,206 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 1.0748 | 1.0 | 2 | 1.0426 | 0.5 | 0.4171 |
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- | 0.9975 | 2.0 | 4 | 0.9763 | 0.6042 | 0.5161 |
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- | 0.9161 | 3.0 | 6 | 0.8952 | 0.75 | 0.7008 |
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- | 0.8879 | 4.0 | 8 | 0.8172 | 0.7917 | 0.7605 |
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- | 0.7693 | 5.0 | 10 | 0.7151 | 0.8333 | 0.8197 |
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- | 0.6634 | 6.0 | 12 | 0.6125 | 0.875 | 0.8692 |
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- | 0.5716 | 7.0 | 14 | 0.5251 | 1.0 | 1.0 |
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- | 0.5056 | 8.0 | 16 | 0.4480 | 1.0 | 1.0 |
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- | 0.4236 | 9.0 | 18 | 0.3784 | 1.0 | 1.0 |
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- | 0.3689 | 10.0 | 20 | 0.3114 | 1.0 | 1.0 |
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- | 0.315 | 11.0 | 22 | 0.2545 | 1.0 | 1.0 |
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- | 0.2559 | 12.0 | 24 | 0.2098 | 1.0 | 1.0 |
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- | 0.198 | 13.0 | 26 | 0.1734 | 1.0 | 1.0 |
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- | 0.1774 | 14.0 | 28 | 0.1441 | 1.0 | 1.0 |
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- | 0.1492 | 15.0 | 30 | 0.1191 | 1.0 | 1.0 |
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- | 0.1216 | 16.0 | 32 | 0.0986 | 1.0 | 1.0 |
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- | 0.0923 | 17.0 | 34 | 0.0822 | 1.0 | 1.0 |
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- | 0.0751 | 18.0 | 36 | 0.0694 | 1.0 | 1.0 |
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- | 0.0716 | 19.0 | 38 | 0.0594 | 1.0 | 1.0 |
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- | 0.0613 | 20.0 | 40 | 0.0513 | 1.0 | 1.0 |
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- | 0.0537 | 21.0 | 42 | 0.0447 | 1.0 | 1.0 |
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- | 0.0436 | 22.0 | 44 | 0.0395 | 1.0 | 1.0 |
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- | 0.0432 | 23.0 | 46 | 0.0351 | 1.0 | 1.0 |
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- | 0.0391 | 24.0 | 48 | 0.0315 | 1.0 | 1.0 |
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- | 0.0337 | 25.0 | 50 | 0.0285 | 1.0 | 1.0 |
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- | 0.03 | 26.0 | 52 | 0.0260 | 1.0 | 1.0 |
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- | 0.0292 | 27.0 | 54 | 0.0238 | 1.0 | 1.0 |
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- | 0.0268 | 28.0 | 56 | 0.0219 | 1.0 | 1.0 |
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- | 0.025 | 29.0 | 58 | 0.0202 | 1.0 | 1.0 |
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- | 0.0219 | 30.0 | 60 | 0.0188 | 1.0 | 1.0 |
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- | 0.0201 | 31.0 | 62 | 0.0176 | 1.0 | 1.0 |
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- | 0.0206 | 32.0 | 64 | 0.0165 | 1.0 | 1.0 |
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- | 0.0191 | 33.0 | 66 | 0.0156 | 1.0 | 1.0 |
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- | 0.0172 | 34.0 | 68 | 0.0147 | 1.0 | 1.0 |
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- | 0.0159 | 35.0 | 70 | 0.0140 | 1.0 | 1.0 |
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- | 0.0159 | 36.0 | 72 | 0.0133 | 1.0 | 1.0 |
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- | 0.014 | 37.0 | 74 | 0.0127 | 1.0 | 1.0 |
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- | 0.0143 | 38.0 | 76 | 0.0121 | 1.0 | 1.0 |
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- | 0.0148 | 39.0 | 78 | 0.0116 | 1.0 | 1.0 |
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- | 0.0127 | 40.0 | 80 | 0.0111 | 1.0 | 1.0 |
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- | 0.0133 | 41.0 | 82 | 0.0107 | 1.0 | 1.0 |
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- | 0.0119 | 42.0 | 84 | 0.0103 | 1.0 | 1.0 |
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- | 0.0129 | 43.0 | 86 | 0.0099 | 1.0 | 1.0 |
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- | 0.012 | 44.0 | 88 | 0.0096 | 1.0 | 1.0 |
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- | 0.0106 | 45.0 | 90 | 0.0092 | 1.0 | 1.0 |
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- | 0.0106 | 46.0 | 92 | 0.0089 | 1.0 | 1.0 |
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- | 0.0108 | 47.0 | 94 | 0.0086 | 1.0 | 1.0 |
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- | 0.0101 | 48.0 | 96 | 0.0083 | 1.0 | 1.0 |
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- | 0.0097 | 49.0 | 98 | 0.0081 | 1.0 | 1.0 |
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- | 0.0098 | 50.0 | 100 | 0.0079 | 1.0 | 1.0 |
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- | 0.0095 | 51.0 | 102 | 0.0076 | 1.0 | 1.0 |
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- | 0.0091 | 52.0 | 104 | 0.0074 | 1.0 | 1.0 |
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- | 0.0084 | 53.0 | 106 | 0.0072 | 1.0 | 1.0 |
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- | 0.009 | 54.0 | 108 | 0.0070 | 1.0 | 1.0 |
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- | 0.0089 | 55.0 | 110 | 0.0068 | 1.0 | 1.0 |
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- | 0.0084 | 56.0 | 112 | 0.0066 | 1.0 | 1.0 |
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- | 0.0081 | 57.0 | 114 | 0.0065 | 1.0 | 1.0 |
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- | 0.0075 | 58.0 | 116 | 0.0063 | 1.0 | 1.0 |
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- | 0.0074 | 59.0 | 118 | 0.0062 | 1.0 | 1.0 |
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- | 0.0075 | 60.0 | 120 | 0.0060 | 1.0 | 1.0 |
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- | 0.0071 | 61.0 | 122 | 0.0059 | 1.0 | 1.0 |
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- | 0.0073 | 62.0 | 124 | 0.0057 | 1.0 | 1.0 |
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- | 0.007 | 63.0 | 126 | 0.0056 | 1.0 | 1.0 |
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- | 0.006 | 64.0 | 128 | 0.0055 | 1.0 | 1.0 |
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- | 0.007 | 65.0 | 130 | 0.0054 | 1.0 | 1.0 |
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- | 0.0067 | 66.0 | 132 | 0.0053 | 1.0 | 1.0 |
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- | 0.0063 | 67.0 | 134 | 0.0051 | 1.0 | 1.0 |
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- | 0.0061 | 68.0 | 136 | 0.0050 | 1.0 | 1.0 |
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- | 0.0062 | 69.0 | 138 | 0.0049 | 1.0 | 1.0 |
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- | 0.0054 | 70.0 | 140 | 0.0048 | 1.0 | 1.0 |
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- | 0.0056 | 71.0 | 142 | 0.0047 | 1.0 | 1.0 |
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- | 0.006 | 72.0 | 144 | 0.0047 | 1.0 | 1.0 |
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- | 0.0057 | 73.0 | 146 | 0.0046 | 1.0 | 1.0 |
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- | 0.0057 | 74.0 | 148 | 0.0045 | 1.0 | 1.0 |
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- | 0.0051 | 75.0 | 150 | 0.0044 | 1.0 | 1.0 |
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- | 0.0053 | 76.0 | 152 | 0.0043 | 1.0 | 1.0 |
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- | 0.0053 | 77.0 | 154 | 0.0043 | 1.0 | 1.0 |
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- | 0.0051 | 78.0 | 156 | 0.0042 | 1.0 | 1.0 |
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- | 0.0053 | 79.0 | 158 | 0.0041 | 1.0 | 1.0 |
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- | 0.0049 | 80.0 | 160 | 0.0040 | 1.0 | 1.0 |
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- | 0.0049 | 81.0 | 162 | 0.0040 | 1.0 | 1.0 |
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- | 0.0047 | 82.0 | 164 | 0.0039 | 1.0 | 1.0 |
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- | 0.0044 | 83.0 | 166 | 0.0039 | 1.0 | 1.0 |
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- | 0.0047 | 84.0 | 168 | 0.0038 | 1.0 | 1.0 |
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- | 0.0044 | 85.0 | 170 | 0.0037 | 1.0 | 1.0 |
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- | 0.0045 | 86.0 | 172 | 0.0037 | 1.0 | 1.0 |
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- | 0.0048 | 87.0 | 174 | 0.0036 | 1.0 | 1.0 |
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- | 0.0045 | 88.0 | 176 | 0.0036 | 1.0 | 1.0 |
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- | 0.0049 | 89.0 | 178 | 0.0035 | 1.0 | 1.0 |
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- | 0.0045 | 90.0 | 180 | 0.0035 | 1.0 | 1.0 |
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- | 0.0043 | 91.0 | 182 | 0.0034 | 1.0 | 1.0 |
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- | 0.0044 | 92.0 | 184 | 0.0034 | 1.0 | 1.0 |
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- | 0.0042 | 93.0 | 186 | 0.0033 | 1.0 | 1.0 |
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- | 0.0039 | 94.0 | 188 | 0.0033 | 1.0 | 1.0 |
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- | 0.0039 | 95.0 | 190 | 0.0033 | 1.0 | 1.0 |
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- | 0.0038 | 96.0 | 192 | 0.0032 | 1.0 | 1.0 |
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- | 0.004 | 97.0 | 194 | 0.0032 | 1.0 | 1.0 |
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- | 0.0037 | 98.0 | 196 | 0.0031 | 1.0 | 1.0 |
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- | 0.0041 | 99.0 | 198 | 0.0031 | 1.0 | 1.0 |
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- | 0.0039 | 100.0 | 200 | 0.0031 | 1.0 | 1.0 |
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- | 0.0041 | 101.0 | 202 | 0.0030 | 1.0 | 1.0 |
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- | 0.0039 | 102.0 | 204 | 0.0030 | 1.0 | 1.0 |
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- | 0.0039 | 103.0 | 206 | 0.0030 | 1.0 | 1.0 |
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- | 0.0037 | 104.0 | 208 | 0.0029 | 1.0 | 1.0 |
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- | 0.0037 | 105.0 | 210 | 0.0029 | 1.0 | 1.0 |
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- | 0.0037 | 106.0 | 212 | 0.0029 | 1.0 | 1.0 |
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- | 0.0037 | 107.0 | 214 | 0.0028 | 1.0 | 1.0 |
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- | 0.0037 | 108.0 | 216 | 0.0028 | 1.0 | 1.0 |
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- | 0.0034 | 109.0 | 218 | 0.0028 | 1.0 | 1.0 |
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- | 0.0036 | 110.0 | 220 | 0.0027 | 1.0 | 1.0 |
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- | 0.0036 | 111.0 | 222 | 0.0027 | 1.0 | 1.0 |
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- | 0.0033 | 112.0 | 224 | 0.0027 | 1.0 | 1.0 |
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- | 0.0034 | 113.0 | 226 | 0.0027 | 1.0 | 1.0 |
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- | 0.0034 | 114.0 | 228 | 0.0026 | 1.0 | 1.0 |
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- | 0.003 | 115.0 | 230 | 0.0026 | 1.0 | 1.0 |
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- | 0.0034 | 116.0 | 232 | 0.0026 | 1.0 | 1.0 |
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- | 0.0034 | 117.0 | 234 | 0.0026 | 1.0 | 1.0 |
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- | 0.0031 | 118.0 | 236 | 0.0025 | 1.0 | 1.0 |
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- | 0.003 | 119.0 | 238 | 0.0025 | 1.0 | 1.0 |
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- | 0.0031 | 120.0 | 240 | 0.0025 | 1.0 | 1.0 |
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- | 0.0032 | 121.0 | 242 | 0.0025 | 1.0 | 1.0 |
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- | 0.0033 | 122.0 | 244 | 0.0025 | 1.0 | 1.0 |
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- | 0.0031 | 123.0 | 246 | 0.0024 | 1.0 | 1.0 |
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- | 0.003 | 124.0 | 248 | 0.0024 | 1.0 | 1.0 |
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- | 0.0033 | 125.0 | 250 | 0.0024 | 1.0 | 1.0 |
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- | 0.0028 | 126.0 | 252 | 0.0024 | 1.0 | 1.0 |
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- | 0.003 | 127.0 | 254 | 0.0024 | 1.0 | 1.0 |
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- | 0.0028 | 128.0 | 256 | 0.0023 | 1.0 | 1.0 |
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- | 0.0028 | 129.0 | 258 | 0.0023 | 1.0 | 1.0 |
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- | 0.0029 | 130.0 | 260 | 0.0023 | 1.0 | 1.0 |
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- | 0.0029 | 131.0 | 262 | 0.0023 | 1.0 | 1.0 |
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- | 0.0029 | 132.0 | 264 | 0.0023 | 1.0 | 1.0 |
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- | 0.003 | 133.0 | 266 | 0.0023 | 1.0 | 1.0 |
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- | 0.0028 | 134.0 | 268 | 0.0022 | 1.0 | 1.0 |
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- | 0.0027 | 135.0 | 270 | 0.0022 | 1.0 | 1.0 |
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- | 0.003 | 136.0 | 272 | 0.0022 | 1.0 | 1.0 |
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- | 0.0028 | 137.0 | 274 | 0.0022 | 1.0 | 1.0 |
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- | 0.0028 | 138.0 | 276 | 0.0022 | 1.0 | 1.0 |
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- | 0.0028 | 139.0 | 278 | 0.0022 | 1.0 | 1.0 |
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- | 0.0029 | 140.0 | 280 | 0.0022 | 1.0 | 1.0 |
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- | 0.0029 | 141.0 | 282 | 0.0022 | 1.0 | 1.0 |
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- | 0.0026 | 142.0 | 284 | 0.0021 | 1.0 | 1.0 |
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- | 0.0027 | 143.0 | 286 | 0.0021 | 1.0 | 1.0 |
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- | 0.0027 | 144.0 | 288 | 0.0021 | 1.0 | 1.0 |
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- | 0.0027 | 145.0 | 290 | 0.0021 | 1.0 | 1.0 |
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- | 0.0028 | 146.0 | 292 | 0.0021 | 1.0 | 1.0 |
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- | 0.0026 | 147.0 | 294 | 0.0021 | 1.0 | 1.0 |
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- | 0.0027 | 148.0 | 296 | 0.0021 | 1.0 | 1.0 |
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- | 0.0027 | 149.0 | 298 | 0.0021 | 1.0 | 1.0 |
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- | 0.0024 | 150.0 | 300 | 0.0020 | 1.0 | 1.0 |
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- | 0.0025 | 151.0 | 302 | 0.0020 | 1.0 | 1.0 |
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- | 0.0028 | 152.0 | 304 | 0.0020 | 1.0 | 1.0 |
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- | 0.0025 | 153.0 | 306 | 0.0020 | 1.0 | 1.0 |
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- | 0.0026 | 154.0 | 308 | 0.0020 | 1.0 | 1.0 |
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- | 0.0027 | 155.0 | 310 | 0.0020 | 1.0 | 1.0 |
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- | 0.0026 | 156.0 | 312 | 0.0020 | 1.0 | 1.0 |
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- | 0.0025 | 157.0 | 314 | 0.0020 | 1.0 | 1.0 |
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- | 0.0025 | 158.0 | 316 | 0.0020 | 1.0 | 1.0 |
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- | 0.0025 | 159.0 | 318 | 0.0020 | 1.0 | 1.0 |
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- | 0.0025 | 160.0 | 320 | 0.0020 | 1.0 | 1.0 |
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- | 0.0025 | 161.0 | 322 | 0.0019 | 1.0 | 1.0 |
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- | 0.0025 | 162.0 | 324 | 0.0019 | 1.0 | 1.0 |
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- | 0.0024 | 163.0 | 326 | 0.0019 | 1.0 | 1.0 |
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- | 0.0026 | 164.0 | 328 | 0.0019 | 1.0 | 1.0 |
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- | 0.0024 | 165.0 | 330 | 0.0019 | 1.0 | 1.0 |
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- | 0.0025 | 166.0 | 332 | 0.0019 | 1.0 | 1.0 |
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- | 0.0024 | 167.0 | 334 | 0.0019 | 1.0 | 1.0 |
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- | 0.0026 | 168.0 | 336 | 0.0019 | 1.0 | 1.0 |
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- | 0.0024 | 169.0 | 338 | 0.0019 | 1.0 | 1.0 |
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- | 0.0024 | 170.0 | 340 | 0.0019 | 1.0 | 1.0 |
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- | 0.0026 | 171.0 | 342 | 0.0019 | 1.0 | 1.0 |
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- | 0.0026 | 172.0 | 344 | 0.0019 | 1.0 | 1.0 |
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- | 0.0025 | 173.0 | 346 | 0.0019 | 1.0 | 1.0 |
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- | 0.0023 | 174.0 | 348 | 0.0019 | 1.0 | 1.0 |
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- | 0.0024 | 175.0 | 350 | 0.0019 | 1.0 | 1.0 |
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- | 0.0023 | 176.0 | 352 | 0.0019 | 1.0 | 1.0 |
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- | 0.0022 | 177.0 | 354 | 0.0019 | 1.0 | 1.0 |
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- | 0.0024 | 178.0 | 356 | 0.0018 | 1.0 | 1.0 |
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- | 0.0024 | 179.0 | 358 | 0.0018 | 1.0 | 1.0 |
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- | 0.0023 | 180.0 | 360 | 0.0018 | 1.0 | 1.0 |
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- | 0.0024 | 181.0 | 362 | 0.0018 | 1.0 | 1.0 |
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- | 0.0023 | 182.0 | 364 | 0.0018 | 1.0 | 1.0 |
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- | 0.0025 | 183.0 | 366 | 0.0018 | 1.0 | 1.0 |
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- | 0.0024 | 184.0 | 368 | 0.0018 | 1.0 | 1.0 |
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- | 0.0023 | 185.0 | 370 | 0.0018 | 1.0 | 1.0 |
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- | 0.0024 | 186.0 | 372 | 0.0018 | 1.0 | 1.0 |
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- | 0.0022 | 187.0 | 374 | 0.0018 | 1.0 | 1.0 |
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- | 0.0025 | 188.0 | 376 | 0.0018 | 1.0 | 1.0 |
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- | 0.0025 | 189.0 | 378 | 0.0018 | 1.0 | 1.0 |
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- | 0.0021 | 190.0 | 380 | 0.0018 | 1.0 | 1.0 |
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- | 0.0023 | 191.0 | 382 | 0.0018 | 1.0 | 1.0 |
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- | 0.0023 | 192.0 | 384 | 0.0018 | 1.0 | 1.0 |
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- | 0.0023 | 193.0 | 386 | 0.0018 | 1.0 | 1.0 |
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- | 0.0022 | 194.0 | 388 | 0.0018 | 1.0 | 1.0 |
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- | 0.0023 | 195.0 | 390 | 0.0018 | 1.0 | 1.0 |
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- | 0.0023 | 196.0 | 392 | 0.0018 | 1.0 | 1.0 |
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- | 0.0022 | 197.0 | 394 | 0.0018 | 1.0 | 1.0 |
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- | 0.0023 | 198.0 | 396 | 0.0018 | 1.0 | 1.0 |
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- | 0.0023 | 199.0 | 398 | 0.0018 | 1.0 | 1.0 |
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- | 0.0024 | 200.0 | 400 | 0.0018 | 1.0 | 1.0 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
19
  It achieves the following results on the evaluation set:
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+ - Loss: 0.0021
21
  - Accuracy: 1.0
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  - F1: 1.0
23
 
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 1.1111 | 1.0 | 2 | 1.0519 | 0.3958 | 0.2245 |
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+ | 1.0223 | 2.0 | 4 | 1.0014 | 0.6042 | 0.4947 |
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+ | 0.9491 | 3.0 | 6 | 0.9297 | 0.6042 | 0.4839 |
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+ | 0.8283 | 4.0 | 8 | 0.8463 | 0.6458 | 0.5689 |
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+ | 0.8 | 5.0 | 10 | 0.7632 | 0.7708 | 0.7583 |
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+ | 0.6775 | 6.0 | 12 | 0.6857 | 0.8333 | 0.8321 |
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+ | 0.6429 | 7.0 | 14 | 0.6167 | 0.9167 | 0.9172 |
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+ | 0.5803 | 8.0 | 16 | 0.5473 | 0.9375 | 0.9381 |
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+ | 0.4597 | 9.0 | 18 | 0.4705 | 0.9792 | 0.9793 |
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+ | 0.3854 | 10.0 | 20 | 0.4016 | 1.0 | 1.0 |
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+ | 0.3427 | 11.0 | 22 | 0.3417 | 1.0 | 1.0 |
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+ | 0.3251 | 12.0 | 24 | 0.2882 | 1.0 | 1.0 |
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+ | 0.2751 | 13.0 | 26 | 0.2398 | 1.0 | 1.0 |
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+ | 0.2163 | 14.0 | 28 | 0.1968 | 1.0 | 1.0 |
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+ | 0.1764 | 15.0 | 30 | 0.1598 | 1.0 | 1.0 |
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+ | 0.1442 | 16.0 | 32 | 0.1304 | 1.0 | 1.0 |
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+ | 0.1209 | 17.0 | 34 | 0.1076 | 1.0 | 1.0 |
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+ | 0.1065 | 18.0 | 36 | 0.0898 | 1.0 | 1.0 |
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+ | 0.0905 | 19.0 | 38 | 0.0757 | 1.0 | 1.0 |
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+ | 0.0717 | 20.0 | 40 | 0.0644 | 1.0 | 1.0 |
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+ | 0.0611 | 21.0 | 42 | 0.0553 | 1.0 | 1.0 |
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+ | 0.0659 | 22.0 | 44 | 0.0481 | 1.0 | 1.0 |
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+ | 0.0451 | 23.0 | 46 | 0.0423 | 1.0 | 1.0 |
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+ | 0.049 | 24.0 | 48 | 0.0376 | 1.0 | 1.0 |
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+ | 0.0414 | 25.0 | 50 | 0.0338 | 1.0 | 1.0 |
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+ | 0.0362 | 26.0 | 52 | 0.0306 | 1.0 | 1.0 |
79
+ | 0.0313 | 27.0 | 54 | 0.0279 | 1.0 | 1.0 |
80
+ | 0.0319 | 28.0 | 56 | 0.0256 | 1.0 | 1.0 |
81
+ | 0.0293 | 29.0 | 58 | 0.0236 | 1.0 | 1.0 |
82
+ | 0.0274 | 30.0 | 60 | 0.0218 | 1.0 | 1.0 |
83
+ | 0.0252 | 31.0 | 62 | 0.0203 | 1.0 | 1.0 |
84
+ | 0.0233 | 32.0 | 64 | 0.0190 | 1.0 | 1.0 |
85
+ | 0.0218 | 33.0 | 66 | 0.0178 | 1.0 | 1.0 |
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+ | 0.0205 | 34.0 | 68 | 0.0168 | 1.0 | 1.0 |
87
+ | 0.0189 | 35.0 | 70 | 0.0160 | 1.0 | 1.0 |
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+ | 0.0183 | 36.0 | 72 | 0.0152 | 1.0 | 1.0 |
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+ | 0.0177 | 37.0 | 74 | 0.0145 | 1.0 | 1.0 |
90
+ | 0.0168 | 38.0 | 76 | 0.0138 | 1.0 | 1.0 |
91
+ | 0.0169 | 39.0 | 78 | 0.0132 | 1.0 | 1.0 |
92
+ | 0.0145 | 40.0 | 80 | 0.0127 | 1.0 | 1.0 |
93
+ | 0.0149 | 41.0 | 82 | 0.0122 | 1.0 | 1.0 |
94
+ | 0.014 | 42.0 | 84 | 0.0117 | 1.0 | 1.0 |
95
+ | 0.013 | 43.0 | 86 | 0.0113 | 1.0 | 1.0 |
96
+ | 0.0128 | 44.0 | 88 | 0.0109 | 1.0 | 1.0 |
97
+ | 0.0122 | 45.0 | 90 | 0.0105 | 1.0 | 1.0 |
98
+ | 0.0116 | 46.0 | 92 | 0.0102 | 1.0 | 1.0 |
99
+ | 0.0121 | 47.0 | 94 | 0.0099 | 1.0 | 1.0 |
100
+ | 0.0107 | 48.0 | 96 | 0.0096 | 1.0 | 1.0 |
101
+ | 0.0107 | 49.0 | 98 | 0.0093 | 1.0 | 1.0 |
102
+ | 0.0111 | 50.0 | 100 | 0.0090 | 1.0 | 1.0 |
103
+ | 0.0106 | 51.0 | 102 | 0.0088 | 1.0 | 1.0 |
104
+ | 0.0102 | 52.0 | 104 | 0.0085 | 1.0 | 1.0 |
105
+ | 0.0096 | 53.0 | 106 | 0.0083 | 1.0 | 1.0 |
106
+ | 0.0104 | 54.0 | 108 | 0.0081 | 1.0 | 1.0 |
107
+ | 0.0096 | 55.0 | 110 | 0.0079 | 1.0 | 1.0 |
108
+ | 0.0095 | 56.0 | 112 | 0.0077 | 1.0 | 1.0 |
109
+ | 0.0099 | 57.0 | 114 | 0.0075 | 1.0 | 1.0 |
110
+ | 0.0096 | 58.0 | 116 | 0.0073 | 1.0 | 1.0 |
111
+ | 0.0085 | 59.0 | 118 | 0.0072 | 1.0 | 1.0 |
112
+ | 0.0091 | 60.0 | 120 | 0.0070 | 1.0 | 1.0 |
113
+ | 0.0084 | 61.0 | 122 | 0.0068 | 1.0 | 1.0 |
114
+ | 0.0087 | 62.0 | 124 | 0.0067 | 1.0 | 1.0 |
115
+ | 0.0076 | 63.0 | 126 | 0.0065 | 1.0 | 1.0 |
116
+ | 0.0077 | 64.0 | 128 | 0.0064 | 1.0 | 1.0 |
117
+ | 0.0081 | 65.0 | 130 | 0.0063 | 1.0 | 1.0 |
118
+ | 0.0071 | 66.0 | 132 | 0.0062 | 1.0 | 1.0 |
119
+ | 0.0073 | 67.0 | 134 | 0.0060 | 1.0 | 1.0 |
120
+ | 0.0075 | 68.0 | 136 | 0.0059 | 1.0 | 1.0 |
121
+ | 0.007 | 69.0 | 138 | 0.0058 | 1.0 | 1.0 |
122
+ | 0.007 | 70.0 | 140 | 0.0057 | 1.0 | 1.0 |
123
+ | 0.0066 | 71.0 | 142 | 0.0056 | 1.0 | 1.0 |
124
+ | 0.0063 | 72.0 | 144 | 0.0055 | 1.0 | 1.0 |
125
+ | 0.0064 | 73.0 | 146 | 0.0054 | 1.0 | 1.0 |
126
+ | 0.0071 | 74.0 | 148 | 0.0053 | 1.0 | 1.0 |
127
+ | 0.007 | 75.0 | 150 | 0.0052 | 1.0 | 1.0 |
128
+ | 0.0061 | 76.0 | 152 | 0.0051 | 1.0 | 1.0 |
129
+ | 0.0061 | 77.0 | 154 | 0.0050 | 1.0 | 1.0 |
130
+ | 0.0058 | 78.0 | 156 | 0.0049 | 1.0 | 1.0 |
131
+ | 0.0056 | 79.0 | 158 | 0.0048 | 1.0 | 1.0 |
132
+ | 0.0063 | 80.0 | 160 | 0.0048 | 1.0 | 1.0 |
133
+ | 0.0059 | 81.0 | 162 | 0.0047 | 1.0 | 1.0 |
134
+ | 0.0059 | 82.0 | 164 | 0.0046 | 1.0 | 1.0 |
135
+ | 0.0054 | 83.0 | 166 | 0.0046 | 1.0 | 1.0 |
136
+ | 0.0052 | 84.0 | 168 | 0.0045 | 1.0 | 1.0 |
137
+ | 0.006 | 85.0 | 170 | 0.0044 | 1.0 | 1.0 |
138
+ | 0.0056 | 86.0 | 172 | 0.0044 | 1.0 | 1.0 |
139
+ | 0.0052 | 87.0 | 174 | 0.0043 | 1.0 | 1.0 |
140
+ | 0.0051 | 88.0 | 176 | 0.0042 | 1.0 | 1.0 |
141
+ | 0.0052 | 89.0 | 178 | 0.0042 | 1.0 | 1.0 |
142
+ | 0.0052 | 90.0 | 180 | 0.0041 | 1.0 | 1.0 |
143
+ | 0.0053 | 91.0 | 182 | 0.0041 | 1.0 | 1.0 |
144
+ | 0.005 | 92.0 | 184 | 0.0040 | 1.0 | 1.0 |
145
+ | 0.005 | 93.0 | 186 | 0.0040 | 1.0 | 1.0 |
146
+ | 0.0052 | 94.0 | 188 | 0.0039 | 1.0 | 1.0 |
147
+ | 0.0051 | 95.0 | 190 | 0.0039 | 1.0 | 1.0 |
148
+ | 0.0045 | 96.0 | 192 | 0.0038 | 1.0 | 1.0 |
149
+ | 0.0047 | 97.0 | 194 | 0.0038 | 1.0 | 1.0 |
150
+ | 0.0049 | 98.0 | 196 | 0.0037 | 1.0 | 1.0 |
151
+ | 0.0045 | 99.0 | 198 | 0.0037 | 1.0 | 1.0 |
152
+ | 0.0044 | 100.0 | 200 | 0.0036 | 1.0 | 1.0 |
153
+ | 0.0045 | 101.0 | 202 | 0.0036 | 1.0 | 1.0 |
154
+ | 0.0044 | 102.0 | 204 | 0.0036 | 1.0 | 1.0 |
155
+ | 0.0048 | 103.0 | 206 | 0.0035 | 1.0 | 1.0 |
156
+ | 0.0043 | 104.0 | 208 | 0.0035 | 1.0 | 1.0 |
157
+ | 0.0043 | 105.0 | 210 | 0.0034 | 1.0 | 1.0 |
158
+ | 0.0043 | 106.0 | 212 | 0.0034 | 1.0 | 1.0 |
159
+ | 0.0043 | 107.0 | 214 | 0.0034 | 1.0 | 1.0 |
160
+ | 0.004 | 108.0 | 216 | 0.0033 | 1.0 | 1.0 |
161
+ | 0.004 | 109.0 | 218 | 0.0033 | 1.0 | 1.0 |
162
+ | 0.0041 | 110.0 | 220 | 0.0033 | 1.0 | 1.0 |
163
+ | 0.0041 | 111.0 | 222 | 0.0032 | 1.0 | 1.0 |
164
+ | 0.0041 | 112.0 | 224 | 0.0032 | 1.0 | 1.0 |
165
+ | 0.0039 | 113.0 | 226 | 0.0032 | 1.0 | 1.0 |
166
+ | 0.0041 | 114.0 | 228 | 0.0031 | 1.0 | 1.0 |
167
+ | 0.0038 | 115.0 | 230 | 0.0031 | 1.0 | 1.0 |
168
+ | 0.0037 | 116.0 | 232 | 0.0031 | 1.0 | 1.0 |
169
+ | 0.0036 | 117.0 | 234 | 0.0031 | 1.0 | 1.0 |
170
+ | 0.0035 | 118.0 | 236 | 0.0030 | 1.0 | 1.0 |
171
+ | 0.0038 | 119.0 | 238 | 0.0030 | 1.0 | 1.0 |
172
+ | 0.0038 | 120.0 | 240 | 0.0030 | 1.0 | 1.0 |
173
+ | 0.0037 | 121.0 | 242 | 0.0029 | 1.0 | 1.0 |
174
+ | 0.0037 | 122.0 | 244 | 0.0029 | 1.0 | 1.0 |
175
+ | 0.0036 | 123.0 | 246 | 0.0029 | 1.0 | 1.0 |
176
+ | 0.0034 | 124.0 | 248 | 0.0029 | 1.0 | 1.0 |
177
+ | 0.0035 | 125.0 | 250 | 0.0029 | 1.0 | 1.0 |
178
+ | 0.0035 | 126.0 | 252 | 0.0028 | 1.0 | 1.0 |
179
+ | 0.0036 | 127.0 | 254 | 0.0028 | 1.0 | 1.0 |
180
+ | 0.0034 | 128.0 | 256 | 0.0028 | 1.0 | 1.0 |
181
+ | 0.0032 | 129.0 | 258 | 0.0028 | 1.0 | 1.0 |
182
+ | 0.0037 | 130.0 | 260 | 0.0027 | 1.0 | 1.0 |
183
+ | 0.0034 | 131.0 | 262 | 0.0027 | 1.0 | 1.0 |
184
+ | 0.0034 | 132.0 | 264 | 0.0027 | 1.0 | 1.0 |
185
+ | 0.0039 | 133.0 | 266 | 0.0027 | 1.0 | 1.0 |
186
+ | 0.0033 | 134.0 | 268 | 0.0027 | 1.0 | 1.0 |
187
+ | 0.0036 | 135.0 | 270 | 0.0027 | 1.0 | 1.0 |
188
+ | 0.0034 | 136.0 | 272 | 0.0026 | 1.0 | 1.0 |
189
+ | 0.0033 | 137.0 | 274 | 0.0026 | 1.0 | 1.0 |
190
+ | 0.0033 | 138.0 | 276 | 0.0026 | 1.0 | 1.0 |
191
+ | 0.003 | 139.0 | 278 | 0.0026 | 1.0 | 1.0 |
192
+ | 0.0035 | 140.0 | 280 | 0.0026 | 1.0 | 1.0 |
193
+ | 0.003 | 141.0 | 282 | 0.0026 | 1.0 | 1.0 |
194
+ | 0.0031 | 142.0 | 284 | 0.0025 | 1.0 | 1.0 |
195
+ | 0.003 | 143.0 | 286 | 0.0025 | 1.0 | 1.0 |
196
+ | 0.0032 | 144.0 | 288 | 0.0025 | 1.0 | 1.0 |
197
+ | 0.0033 | 145.0 | 290 | 0.0025 | 1.0 | 1.0 |
198
+ | 0.0032 | 146.0 | 292 | 0.0025 | 1.0 | 1.0 |
199
+ | 0.0031 | 147.0 | 294 | 0.0025 | 1.0 | 1.0 |
200
+ | 0.0032 | 148.0 | 296 | 0.0024 | 1.0 | 1.0 |
201
+ | 0.0029 | 149.0 | 298 | 0.0024 | 1.0 | 1.0 |
202
+ | 0.0032 | 150.0 | 300 | 0.0024 | 1.0 | 1.0 |
203
+ | 0.0028 | 151.0 | 302 | 0.0024 | 1.0 | 1.0 |
204
+ | 0.003 | 152.0 | 304 | 0.0024 | 1.0 | 1.0 |
205
+ | 0.0033 | 153.0 | 306 | 0.0024 | 1.0 | 1.0 |
206
+ | 0.0029 | 154.0 | 308 | 0.0024 | 1.0 | 1.0 |
207
+ | 0.0031 | 155.0 | 310 | 0.0024 | 1.0 | 1.0 |
208
+ | 0.003 | 156.0 | 312 | 0.0024 | 1.0 | 1.0 |
209
+ | 0.0032 | 157.0 | 314 | 0.0023 | 1.0 | 1.0 |
210
+ | 0.0029 | 158.0 | 316 | 0.0023 | 1.0 | 1.0 |
211
+ | 0.0029 | 159.0 | 318 | 0.0023 | 1.0 | 1.0 |
212
+ | 0.0032 | 160.0 | 320 | 0.0023 | 1.0 | 1.0 |
213
+ | 0.0029 | 161.0 | 322 | 0.0023 | 1.0 | 1.0 |
214
+ | 0.0028 | 162.0 | 324 | 0.0023 | 1.0 | 1.0 |
215
+ | 0.003 | 163.0 | 326 | 0.0023 | 1.0 | 1.0 |
216
+ | 0.0029 | 164.0 | 328 | 0.0023 | 1.0 | 1.0 |
217
+ | 0.0026 | 165.0 | 330 | 0.0023 | 1.0 | 1.0 |
218
+ | 0.0029 | 166.0 | 332 | 0.0023 | 1.0 | 1.0 |
219
+ | 0.003 | 167.0 | 334 | 0.0023 | 1.0 | 1.0 |
220
+ | 0.0028 | 168.0 | 336 | 0.0022 | 1.0 | 1.0 |
221
+ | 0.0028 | 169.0 | 338 | 0.0022 | 1.0 | 1.0 |
222
+ | 0.0029 | 170.0 | 340 | 0.0022 | 1.0 | 1.0 |
223
+ | 0.0028 | 171.0 | 342 | 0.0022 | 1.0 | 1.0 |
224
+ | 0.0027 | 172.0 | 344 | 0.0022 | 1.0 | 1.0 |
225
+ | 0.0028 | 173.0 | 346 | 0.0022 | 1.0 | 1.0 |
226
+ | 0.0028 | 174.0 | 348 | 0.0022 | 1.0 | 1.0 |
227
+ | 0.0027 | 175.0 | 350 | 0.0022 | 1.0 | 1.0 |
228
+ | 0.0028 | 176.0 | 352 | 0.0022 | 1.0 | 1.0 |
229
+ | 0.0028 | 177.0 | 354 | 0.0022 | 1.0 | 1.0 |
230
+ | 0.0029 | 178.0 | 356 | 0.0022 | 1.0 | 1.0 |
231
+ | 0.003 | 179.0 | 358 | 0.0022 | 1.0 | 1.0 |
232
+ | 0.0028 | 180.0 | 360 | 0.0022 | 1.0 | 1.0 |
233
+ | 0.0026 | 181.0 | 362 | 0.0022 | 1.0 | 1.0 |
234
+ | 0.0029 | 182.0 | 364 | 0.0022 | 1.0 | 1.0 |
235
+ | 0.0026 | 183.0 | 366 | 0.0022 | 1.0 | 1.0 |
236
+ | 0.0028 | 184.0 | 368 | 0.0022 | 1.0 | 1.0 |
237
+ | 0.0031 | 185.0 | 370 | 0.0022 | 1.0 | 1.0 |
238
+ | 0.0029 | 186.0 | 372 | 0.0022 | 1.0 | 1.0 |
239
+ | 0.0027 | 187.0 | 374 | 0.0021 | 1.0 | 1.0 |
240
+ | 0.0028 | 188.0 | 376 | 0.0021 | 1.0 | 1.0 |
241
+ | 0.0029 | 189.0 | 378 | 0.0021 | 1.0 | 1.0 |
242
+ | 0.0028 | 190.0 | 380 | 0.0021 | 1.0 | 1.0 |
243
+ | 0.0028 | 191.0 | 382 | 0.0021 | 1.0 | 1.0 |
244
+ | 0.0026 | 192.0 | 384 | 0.0021 | 1.0 | 1.0 |
245
+ | 0.0026 | 193.0 | 386 | 0.0021 | 1.0 | 1.0 |
246
+ | 0.0026 | 194.0 | 388 | 0.0021 | 1.0 | 1.0 |
247
+ | 0.0027 | 195.0 | 390 | 0.0021 | 1.0 | 1.0 |
248
+ | 0.003 | 196.0 | 392 | 0.0021 | 1.0 | 1.0 |
249
+ | 0.0029 | 197.0 | 394 | 0.0021 | 1.0 | 1.0 |
250
+ | 0.0027 | 198.0 | 396 | 0.0021 | 1.0 | 1.0 |
251
+ | 0.0029 | 199.0 | 398 | 0.0021 | 1.0 | 1.0 |
252
+ | 0.0027 | 200.0 | 400 | 0.0021 | 1.0 | 1.0 |
253
 
254
 
255
  ### Framework versions